Consumer intention toward online grocery shopping during the post-pandemic (Covid-19)
Purpose: The study investigates the factors that influence consumers’ online grocery purchase intention during the post-pandemic of Covid-19 in Sri Lanka.
Design/methodology/approach: Primary data was collected using a pre-tested structured questionnaire. Data was gathered based on 5 variables and the Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) were applied to analyze the empirical data of 200 respondents. And twenty-five indicators were used to measure the five variables. Further, the study uses Statistical Package for the Social Sciences (SPSS 25) and Analysis of Moment Structures (AMOS 26) to conduct the analysis.
Findings: The study found significant factors that affect consumers’ online grocery purchase intention. The results revealed that Perceived Ease of Use and Perceived Usefulness have a positive and significant impact on the online Purchase Intention of consumers while Perceived Risk represents a negative and insignificant effect on the online grocery purchase intention of consumers. Further, Hedonic Motivation did not affect the online purchase intention of consumers.
Originality: This study represents the online grocery purchase intention among consumers by investigating consumer behavior during and after the Covid-19 pandemic by using the technology acceptance model as a guiding theory.
Implications: The research is based on the expansion of the Technology Acceptance Model (TAM). Besides, the variable “perceived risk” is added to identify the factors that affect consumers’ online shopping intentions. The study confirmed the significant influence of perceived usefulness, perceived ease of use, and hedonic motivation on the continuance usage of online grocery purchasing during the post-pandemic of Covid-19. Moreover, online retailers should improve their online platforms to address the consumers’ increasing demand for online grocery purchasing.
Keywords: Online grocery shopping, Post pandemic, Structural equation modeling, Technology acceptance model